RDSC-5610 Multi-source documentation fixes

content/integrate/redis-data-integration/installation/migration-classic-to-flink.md

@@ -17,7 +17,7 @@ weight: 35
 ---
 
 RDI ships with two stream processor implementations. The *classic*
-processor is implemented in Python. The *Flink* processor is built on top of
+processor is implemented in Python. The default *Flink* processor is built on top of
 [Apache Flink](https://flink.apache.org/). Both run on VM and Kubernetes
 installations. The Flink processor can achieve much higher throughput
 during snapshots, scales horizontally by changing the number of TaskManager replicas,
@@ -99,11 +99,9 @@ redis-di deploy --dir <pipeline-config-directory>
 
 Wait for the deployment to finish and the source collector to stop. Keep
 the pipeline active so the classic processor can process the remaining input records.
-Do not use `redis-di stop` for this step, because it also stops the processor.
 
 Applications can continue writing to the source database while collection
-is disabled. Make sure the database change log retains the whole paused
-interval. When the collector restarts, it resumes from the saved source
+is disabled. When the collector restarts, it resumes from the saved source
 position and processes those changes.
 
 ## Step 3: Wait for the input streams to empty
@@ -118,14 +116,11 @@ Do not include DLQ streams. Use any of the following methods.
 Run:
 
 ```bash
-redis-di describe default
+redis-di describe
 ```
 
 In the **Statistics** table, the **Pending** value for each classic processor
-stream is its current length. Confirm that every input stream is listed and
-that the values agree with the Redis command checks below. This **Pending**
-value is different from consumer-group pending entries. `XPENDING` or group
-lag of `0` alone does not prove that a stream is empty.
+stream is its current length. Confirm that every input stream is listed.
 
 ### Check with Redis commands
 
@@ -156,24 +151,6 @@ XLEN <input-stream-key>
 
 Run a complete `SCAN` and all `XLEN` commands in each of the three checks.
 
-### Check with Redis Insight
-
-1.  Connect Redis Insight to the RDI database and open **Browse**.
-1.  Filter by the pipeline's input stream pattern. For the default pipeline,
-    use `data:{rdi}:*`. Confirm that all input streams are listed.
-1.  Open each stream, select **Stream Data**, and use the refresh button.
-    Confirm that **Entries** is `0`.
-1.  Repeat the complete inventory and entry check three times, five seconds
-    apart.
-
-You can also open the built-in **CLI** and run the `SCAN` and `XLEN` commands
-shown above. The Browser and CLI results must contain the same streams and
-lengths.
-
-If records remain, keep the classic processor running and resolve its
-processing errors before continuing. Do not delete stream entries, reset the
-pipeline, or move consumer-group positions to make the count reach `0`.
-
 ## Step 4: Switch processors and resume collection
 
 After the drain check passes, remove the source's `active: false` setting
@@ -262,7 +239,7 @@ for the `ServiceMonitor` configuration and the available metrics.
 
 ## Rolling back
 
-To revert a pipeline to the classic processor, set `processors.type` back to
+To revert a pipeline to the classic processor, set `processors.type` to
 `classic` and redeploy the pipeline. This setting is required on RDI 2.0.0,
 where the default is `flink`. The classic processor silently ignores
 `processors.advanced`, so you don't need to remove it before switching back.

content/integrate/redis-data-integration/installation/upgrade.md

@@ -21,23 +21,6 @@ Before upgrading to RDI 2.0.0, review the
 [processor default change](#upgrading-to-rdi-200).
 {{< /note >}}
 
-## Upgrading to RDI 2.0.0
-
-RDI 2.0.0 changes the default processor from `classic` to `flink`. This default
-applies when the pipeline's `config.yaml` omits `processors.type`.
-
-For an existing classic pipeline, choose one of these options before upgrading:
-
-- To migrate to Flink, first follow
-  [Migrate from the classic processor to the Flink processor]({{< relref "/integrate/redis-data-integration/installation/migration-classic-to-flink" >}})
-  on RDI 1.19.0. This stops the collector and drains the input streams before
-  switching processors. Then upgrade RDI.
-- To keep the classic processor, set `processors.type: classic` in the
-  pipeline's `config.yaml` and deploy it before upgrading.
-
-If your pipeline already uses `processors.type: flink`, no processor change
-is needed. Continue with the upgrade instructions for your installation.
-
 ## Upgrading a VM installation
 
 Follow the steps below to upgrade an existing
@@ -254,11 +237,12 @@ The
 fully supported on both VM and Kubernetes installations after upgrading to
 RDI 1.19.0. Once the upgrade completes, it is always available —
 no opt-in is required, and the defaults are sized for typical workloads.
-On RDI 1.19.0, existing classic pipelines keep using that processor until
-you switch them by setting
+
+{{< warning >}}The Flink processor is the default as of RDI 2.0.0.
+Upgrading to that release or later moves a pipeline whose `config.yaml` does not set
 [`processors.type`]({{< relref "/integrate/redis-data-integration/data-pipelines/pipeline-config#processors" >}})
-to `flink` in their `config.yaml`.
-RDI 2.0.0 changes this default; see [Upgrading to RDI 2.0.0](#upgrading-to-rdi-200).
+onto the Flink processor when you next deploy it. To keep such a pipeline on the classic
+processor, set `processors.type` to `classic` before you upgrade.{{< /warning >}}
 
 On Kubernetes, to override the Flink processor defaults, add an
 `operator.dataPlane.flinkProcessor` block to your `rdi-values.yaml` file as